The nonlinear offline model of the controlled plant is built by LS-SVM with the radial basis function (RBF) kernel.

首先，用具有RBF核函数的LS-SVM离线建立被控对象的非线性模型；

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The different classification kernel functions are compared, and analysis shows that the radial base function most suits the corn leaf disease classification recognition.

不同的分类核函数的相互比较分析表明，径向基核函数最适合玉米病害的分类识别。

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Then, experiments with the radial basic function and the polynomial kernel function are used to reveal the relationship between kernel functions and the filter algorithm.

接着分别针对径向基核函数和多项式核函数进行多次实验，分析这两种核函数对过滤算法的影响。

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